Population structure, differential bias and genomic control in a large-scale, case-control association study
| Autor: | Rebecca Pask, Martin Moorhead, Lisa M. Maier, David Clayton, Joanna M. M. Howson, Paul Hardenbol, Deborah J. Smyth, Helen Stevens, John A. Todd, Malek Faham, Thomas D. Willis, Hywel B. Jones, Nigel R. Ovington, Alex C. Lam, Jason D. Cooper, Sarah Nutland, Neil Walker, Luc J. Smink, Matthew Falkowski |
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| Rok vydání: | 2005 |
| Předmět: |
Adolescent
Genotype media_common.quotation_subject Population Genomics Single-nucleotide polymorphism Biology Polymorphism Single Nucleotide Bias Statistics Genetics SNP Humans False Positive Reactions Lymphocytes education media_common Selection bias education.field_of_study Models Genetic Confounding DNA United Kingdom Diabetes Mellitus Type 1 Genetics Population Causal inference Case-Control Studies |
| Zdroj: | Nature genetics. 37(11) |
| ISSN: | 1061-4036 |
| Popis: | The main problems in drawing causal inferences from epidemiological case-control studies are confounding by unmeasured extraneous factors, selection bias and differential misclassification of exposure. In genetics the first of these, in the form of population structure, has dominated recent debate. Population structure explained part of the significant +11.2% inflation of test statistics we observed in an analysis of 6,322 nonsynonymous SNPs in 816 cases of type 1 diabetes and 877 population-based controls from Great Britain. The remainder of the inflation resulted from differential bias in genotype scoring between case and control DNA samples, which originated from two laboratories, causing false-positive associations. To avoid excluding SNPs and losing valuable information, we extended the genomic control method by applying a variable downweighting to each SNP. |
| Databáze: | OpenAIRE |
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